IoT-Based Sensor Shoes System for Gait Correction

Abstract

Since the 2000s, diseases that tend to occur in high-age groups such as degenerative arthritis and intervertebral disk has been gradually increasing in low-age groups due to incorrect gait or bad habits. One of the fundamental problems with these results can be found in an indifference to gait. This study aimed at determining the walking styles through pressure sensor. It uses a three-axis accelerometer and a gyro sensor to identify pigeon-toed walking and splay-footed walking. The system can monitor gait using the sensor data stored in the PC and smartphone applications transferred via Bluetooth. This can be visually confirmed through color changes in accordance with the sensor value with the neo-pixels. Research developments can analyze the type of gait as compared to the value for the case of incorrect gait based on normal pace with the acceleration value through the sensor. Through the experiment, the recognition rate capable of distinguishing in toeing gait was 56.25%, and out toeing gait was 81.25%. The system of this paper continuously collects gait data to enable monitoring whenever and wherever users want. It is easy to check when and where users walked with a normal gait or abnormal gait, and it is expected to help users manage their gait. This system may be approached as a precautionary measure by notifying other parts of the body that there is an abnormality in asymmetric walking (walking with differences in speed, angle, and stride of both feet) or when dragging feet.